NCT07021235: aiinane-24-1

Proof of Concept of the Aiinane Preoperative Risk Assessment Tool.

Completed Last updated 31 July 2025

What this trial tests

trial in Breast Neoplasms in 30 participants. Completed in 25 July 2025.

Timeline

3 March 2025

Primary endpoint
25 July 2025

25 July 2025

Quick facts

Lead sponsor	Ancor Serrano
Status	Completed
Study type	OBSERVATIONAL
Enrollment	30
Start date	3 March 2025
Primary completion	25 July 2025
Estimated completion	25 July 2025
Sites	1 location across Spain

Conditions studied

• Breast Neoplasms — all drugs for Breast Neoplasms →
• Surgery Scheduled — all drugs for Surgery Scheduled →
• Surgery Related Complications Rate — all drugs for Surgery Related Complications Rate →
• Preanesthetic Medication — all drugs for Preanesthetic Medication →

Sponsor

Ancor Serrano

Who can join

18 and older, any sex, with Breast Neoplasms or Surgery Scheduled. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

BACKGROUND: Each year, over 13,000 patients in Catalonia and more than 4 million worldwide experience last-minute surgery cancellations (LMC) due to preoperative inefficiencies. As anaesthesia services struggle to meet surgical demands, thorough preoperative evaluations become challenging. Current resource-intensive pre-anaesthetic assessments are undermined by high demand, causing inefficiency. However, proper assessment identifies that most patients (\>70%) are low-risk and ensures high-risk patients are adequately prepared by analyzing risk profiles, health status, medical history, treatment, and lab results.

RATIONALE: Previous attempts to improve preoperative risk assessment have mainly relied on self-administered questionnaires to detect at-risk patients. The investigators have identified a care model that enhances quality by adding value to preoperative risk assessment. By combining anaesthesiology expertise with AI techniques, the investigators developed an automated digital environment to detect risks, optimize visits, avoid cancellations, and reduce postoperative complications. This system uses parameterized medical knowledge to verify responses and objectively assess patient risk by integrating multiple data sources.

The investigators have developed a Class IIa active diagnostic and monitoring product, a Medical Device Software (MDSW, EMDN V92), to support clinical decision-making in an automated digital preoperative environment. It helps assess patients and flags low-risk from medium/high-risk individuals, reporting personalized needs to the medical team. The software was developed exclusively by independent researchers from Bellvitge University Hospital and the Bellvitge Biomedical Research Institute (IDIBELL).

HYPOTHESIS: The tool has been tested successfully on fictitious patients in controlled preclinical scenarios. The aim now is a proof-of-concept study to verify its performance with real patients in uncontrolled, real-world settings.

This is a Clinical Performance Research Study, aligned with MDSW Clinical Evaluation Guidelines (MDR, MDCG 2020-1) for (EU) 2017/745, and authorized by the Spanish Agency of Medicines and Medical Devices (AEMPS) and the local Ethics Committee.

MAIN OBJECTIVE: The clinical trial aims to verify that the software (aiinane), supporting preanesthetic assessment and preoperative risk estimation, is fit for its intended purpose and performs as expected under normal conditions of use.

This is an observational, non-interventional, single-center, prospective, longitudinal adult cohort study. The target population is any adult (\>18 years) of any gender undergoing breast cancer surgery.

Publications & conference data

No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.